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Estimands and inference in cluster-randomized vaccine trials.

Kayla W KilpatrickMichael G HudgensM Elizabeth Halloran
Published in: Pharmaceutical statistics (2020)
Cluster-randomized trials are often conducted to assess vaccine effects. Defining estimands of interest before conducting a trial is integral to the alignment between a study's objectives and the data to be collected and analyzed. This paper considers estimands and estimators for overall, indirect, and total vaccine effects in trials, where clusters of individuals are randomized to vaccine or control. The scenario is considered where individuals self-select whether to participate in the trial, and the outcome of interest is measured on all individuals in each cluster. Unlike the overall, indirect, and total effects, the direct effect of vaccination is shown in general not to be estimable without further assumptions, such as no unmeasured confounding. An illustrative example motivated by a cluster-randomized typhoid vaccine trial is provided.
Keyphrases
  • phase iii
  • phase ii
  • open label
  • double blind
  • clinical trial
  • placebo controlled
  • study protocol
  • machine learning
  • big data
  • single cell